7239 results for "canc*"

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• Childhood Cancer Data Initiative (CCDI): Molecular Characterization Initiative

  The National Cancer Institute's (NCI) Childhood Cancer Data Initiative (CCDI) focuses on the critical need to collect, analyze, and share data to address the burden of cancer in children, adolescents, and young adults (AYAs). The Molecular Characterization Initiative (MCI) will further the CCDI's goals by providing access to better diagnostic tests for pediatric and AYA patients. The molecular characterizations of solid tumors, soft tissue sarcomas, and rare diseases are performed in a CLIA-certified setting as results may be used to screen for and/or confirm clinical trial eligibility, direct treatment, or otherwise contribute to the conduct of the trial. The following molecular characterization assays were performed:Tumor/Normal Whole Exome sequencing Methylation arraysArcher fusion panel Deidentified clinical reportsNote: New data will be added periodically, please check the CCDI Hub Explore site for updates.

  Study phs002790

• Identification and phenotypic characterization of neoantigen-specific cytotoxic CD4+ T cells in endometrial cancer

  Tumor-reactive CD4+ T cells often accumulate in the tumor microenvironment (TME) in human cancer, but their functions and roles in anti-tumor responses remain elusive. Here, we investigated the immunopeptidome of HLA class II (HLA-II)-positive endometrial cancer with inflamed TME using a proteogenomic approach. We identified HLA-II neoantigens, one of which induced polyclonal CD4+ tumor-infiltrating lymphocyte (TIL) responses. We experimentally demonstrate that neoantigen-specific CD4+ TILs lyse target cells in an HLA-II-dependent manner. Single cell analysis of the TME coupled with T cell receptor (TCR) sequencing revealed the presence of CD4+ T cell clusters characterized by CXCL13 expression. The CXCL13+ clusters contained two subclusters with distinct cytotoxic gene expression patterns. The identified neoantigen-specific CD4+ T cells were found exclusively in one of the CXCL13-positive subclusters characterized by GZMB and CCL5 expression. These results demonstrate the involvement of tumor reactive CD4+ T cells with cytotoxic function in immune surveillance of endometrial cancer and reveal their transcriptomic signature.

  Study JGAS000766

• Breast cancer sequencing data

  Study EGAS00001007336

• Spatial transcriptomics analysis of triple negative breast cancers

  While triple negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigated TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We performed an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures led to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identified nine TNBC ecotypes, further validated in external datasets. Several ecotypes were associated with disease outcome and characterized by potentially actionable features. In this work, we provideThis is the largest TNBC series providing a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. All the processed data needed to replicate the results from the publication (counts, images, clinical data, etc) are available on Zenodo: https://zenodo.org/records/14204217

  Study EGAS50000000475

• Spatial transcriptomics analysis of triple negative breast cancers

  Spatial transcriptomics analysis of triple negative breast cancers Both bulk sequencing and ST were performed Counts, images etc are available at https://zenodo.org/doi/10.5281/zenodo.8135721

  Dataset EGAD50000000686

• Human prostate cancer plasma cfRNA study - raw data

  mRNA capture sequencing on plasma sample from 132 prostate cancer patients and 48 control donors.

  Study EGAS50000001265

• prostate cancer plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 180 different human donors: 132 prostate cancer patients (PRAD) and 48 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001805

• non-malignant plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 125 different human donors: 88 patients with a non-malignant disease and 37 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001806

• Repertoire and clinical hierarchy of AR locus alterations in castration-resistant prostate cancer

  Somatic alterations to the androgen receptor (AR) gene are pivotal drivers of treatment resistance in metastatic castration-resistant prostate cancer (mCRPC), but their prevalence, clinical impact, and etiology remain incompletely understood. Here, we analyzed 3399 plasma cell-free DNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients with matched clinical data and extensive AR locus coverage.

  Study EGAS50000001101

• Targeted Illumina sequencing of 3399 plasma cfDNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients

  Blood samples were collected from eight clinical trials and a British Columbia-based biobank. All plasma cfDNA and leukocyte DNA samples were processed with uniform methodology, and underwent targeted sequencing using a custom hybridization capture panel and Illumina instruments. Four different generations of custom hybridization capture panel were used, all providing coverage of the complete coding regions of 72 prostate cancer genes, and later panel generations also providing exhaustive coverage of the AR locus (including introns and flanking regulatory regions), as well as a genome-wide SNP grid for copy number analysis.

  Dataset EGAD50000001594